M-insurance Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

Mobile Insurance Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile... Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on M

Mobile Insurance

Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile

Disclaimer:

The copyright of this document rests with the author The views expressed in this thesis are those of the author and do not necessarily express the views of the Delft University of Technology or Deloitte consulting

Overcoming Privacy Concerns in the Consumer Use of Insurance Services based on Mobile Technologies

Chair: Prof Dr Yao-Hua Tan – ICT section

Officious Chair: Prof Dr W.A.G.A Bouwman – ICT section

First Supervisor: Dr ir G.A Reuver MSc – ICT section

Second Supervisor: Dr ir M Kroesen TLO section

External Supervisor: Drs A Beers – Deloitte Consulting

External Supervisor: A Mahawat Khan MSc – Deloitte Consulting

“Science and technology revolutionize our lives, but memory, tradition and myth frame our response” – Arthur M Schlesinger Jr

Acknowledgements

This thesis marks the final step for the completion of my Master System Engineering, Policy Analysis and Management (SEPAM) at the Delft University of Technology This graduation project started in May 2014 intern at Deloitte Consulting and since that moment a significant part of my life has been spent on this thesis Therefore, I am proud to present the final version of my thesis

First, I would like to express my gratitude to my graduation committee for their great support last seven months I would like to thank Assistant Professor Mark de Reuver, my first supervisor, for his general support in both theoretical and practical field I would like to thank Assistant Professor Maarten Kroesen, my second supervisor, for his sharpening insights in the statistical methodologies and Professor Harry Bouwman for chairing my graduation committee

Second, I would like to thank Deloitte Consulting for giving me the great opportunity to conduct my master thesis intern Your innovative and progressive mindset helped me to finalize this thesis I would like to express special thanks to Arjen Beers and Amira Mahawat Khan for their feedback, enjoyable way of working and involving me in the business of mobile insurance

Third, I would like to thank my friends and family for their support during my graduation Special thanks to my friends, siblings and (former) roommates for lending their listening ears and encouragement, my parents for bringing me to this point in life and my girlfriend for giving me the freedom and loving support required for this accomplishment

I hope you all enjoy reading the result,

Amsterdam, December 2014,

Sebastian Derikx

List of Acronyms

AV Additional insurance offerings

B1/B2 Relative consumer saving

BMT Business Model Transformations (innovation)

CSMIS Context Sensitive Mobile Insurance Services

CSMS Context Sensitive Mobile Services

DOI Diffusion of innovation

FSI Financial Service Industry

GR Third party advertisement

IID Independently and Identically Distributed

M-Insurance Mobile insurance

MNL-model Multinomial logit model

MOE Margin of error

SEM Structural Equation modeling

Management summary:

Research problem

Ongoing digitalization results in both threats as opportunities for the insurance sector Increased transparency stimulates switching behavior and shifts the insurance market to a more price based competition Together with recent developments such as the ban on intermediary commissions and the separation of banking and insurance activities, the traditional business model is put under pressure By fully reaping the benefits of mobile technologies, such as portability, social interactivity, context sensitivity, connectivity and individuality, a variety of opportunities for innovative insurance services arises A more differentiated product portfolio can shift the price based competition to a more quality focus which enables insurers to operate in more niche markets focusing on higher margins

In the last few years, privacy concerns associated with the consumer use of mobile technologies, have been the subject of many research papers A number of privacy studies empirically verified the negative effect of perceived privacy concerns on the intention of use online and mobile services As the disclosure of personal information is often necessary in obtaining online and mobile services, privacy concerns could inhibit people’s intention to use them as well This could have major implications for the adoption of mobile insurance since privacy concerns regarding the insurance industry are already relatively high in general Therefore, it is essential, in the development of future mobile insurance services, to understand the role of associated privacy concerns Accordingly, this study aims to increase understanding of mobile insurance related privacy concerns, its relation on consumer’s ‘likelihood of use’ and potential compensating factors as perceived usefulness and

expected monetary benefits Therefore, the objective of this research is to further develop

understanding towards the mitigating effect of perceived usefulness and monetary rewards on privacy concerns regarding the likelihood of use for mobile insurance services In line with this objective the

following main research question is developed:

RQ In what way can privacy concerns, affecting the likelihood of use mobile insurance services,

be mitigated by expected monetary benefits and perceived usefulness?

Domain on Mobile Insurance

For a clear and consistent understanding of this research question the definition of mobile insurance

for this study is defined as “insurance products and services based on context sensitive mobile

technologies” Hereby insurance products and services involve all direct customer focused activities

of an insurer Thus, both the insurance policy itself and supportive services are involved Context sensitivity of mobile technologies involves the ability to both gather and respond to real or simulated data unique to current location, environment, and time

Mobile insurance covers a broad field of insurance services In order to get a better understanding on the scope of mobile insurance a categorization is made This categorization is based on an explorative scan to all worldwide mobile insurance services These worldwide mobile insurance services are subsequently categorized on its consumer functionalities and validated with insurance industry and technology experts The final categorization, with a brief elaboration per category is listed below:

4 Preventative

information services;

Consumer context information offers insurers the opportunity to provide consumers with relevant context related preventative information

5 Accident detection &

prevention;

By detecting (potential) accidents as early as possible, damages could

be prevented and minimized

6 Mobile accessibility; Mobile technologies facilitate a communication channel for sales and

services

7 Personal dashboards; By measuring individual behavior, insight could be provided in risk

profiles of consumers to increase risk awareness

8 Additional

informative services;

Context sensitive information offers opportunities for several insurance services

semi-Theoretical background on the concept of privacy

Within literature a variety of definitions and interpretations for privacy is present, however a unified account of privacy has yet to emerge This study interprets the definition of privacy as a tradable interest; “an interest that individuals have in sustaining a ‘personal space’ free from interference by other people and organizations” Subsequently, this definition is operationalized to facilitate the measurement of privacy A commonly used (reverse) operationalization of privacy in literature is the measurement of privacy concerns Therefore, privacy is measured in this study by privacy concerns Due to its plurality and inconsistency, a unified account for privacy is still absent in literature Some scholars used another approach and instead of searching for an inclusive definition of privacy, they developed a typology for privacy Recent literature defined seven types of privacy of which three are relevant for the application of (current) mobile insurance:

Privacy of location and space "The right to move about in public or semi-public space without being

identified, tracked, or monitored."

Privacy of behavior and action "The ability to behave in public, semi-public or one’s private space

without having actions monitored or controlled by others."

Privacy of data and image "Concerns about making sure that individuals’ data is not automatically

available to other individuals and organizations and that people can exercise a substantial degree of control over that data and its use.”

A majority of consumers considers the disclosure of personal information as essential in modern life The disclosure of personal information is however contrary with the definition of privacy; sustaining a

‘personal space’ Consequently, numerous studies consistently concluded that people are very concerned about their online privacy Aforementioned contradiction imply that individuals consider a utilitarian trade-off between perceived benefits and sacrifices of disclosing personal information Hereby privacy concerns have to be considered as a sacrifice Previous literature states that providers can mitigate the negative effect of privacy concerns on the ‘likelihood of use’ in two ways; (1) by offering privacy policies regarding the handling and use of personal information and (2) by offering benefits such as monetary rewards or convenience These compensating are further operationalized

as expected monetary benefits and perceived usefulness

No existence of a direct relation between the construct of privacy concerns, perceived usefulness and expected monetary benefits is found in literature However, several IT adoption studies

in literature suggest an indirect relation through the construct of likelihood of use Hereby, the likelihood of use is positively affected by the perceived usefulness and expected monetary benefits and negatively affected by privacy concerns These findings are combined in a conceptual model which

is validated for the case of mobile insurance by the explorative assessment

Analysis and results

In order to provide an answer on the main research question, two quantitative assessments are conducted By means of a consumer survey and multiple regression, an explorative assessment is conducted to the relations between the constructs of likelihood of use, privacy concerns, perceived usefulness and expected monetary benefit Hereby, the conceptual model is validated

By means of a conjoint survey, a more in-depth assessment to the buy-off value of privacy is conducted for all relevant types of privacy, for the case of Pay-As-You-Drive (PAYD) insurance An overview of both assessments is provided in Table 0.1

Table 0.1: Overview assessments

Explorative assessment: Conjoint assessment

(stated-choice)

to raise more interest of consumers for future use

The relation between the construct of expected monetary benefits and the likelihood of use shows to be positive as well, however not significant for all categories of mobile insurance Expected monetary benefits appear not to be a significant predictor for the use of mobile accessibility Overall

it can be concluded that mobile insurance services with a higher expected monetary benefit for the consumer are likely to raise more interest of consumers for future use

In contrast to previous constructs, the relationship between the construct of privacy concerns and the likelihood of use appears to be negative, however not significant for all categories of mobile insurance Privacy concerns appear not to be a significant predictor for the use of Accident detection and prevention and Mobile accessibility Overall it can be concluded that mobile insurance service with raised privacy concerns are likely to have a negative impact on the likelihood of use mobile insurance

Altogether, it can be concluded that the likelihood of use mobile insurance services is primarily driven

by its perceived usefulness Thereafter, consumers’ likelihood of use mobile insurance services is driven by raised expectations on accompanied monetary benefits and inhibited by increased privacy concerns However, not for every category of mobile insurance the predictors have a significant relation with the likelihood of use, no significant contra relations are found These findings seem to support the relations as found in literature

Conjoint assessment

Although the explorative assessment shows us that monetary benefits are not the strongest predictor for consumers’ likelihood of use mobile insurance services, the conjoint assessment is used for a more in-depth analysis to the buy-off value of privacy For this analysis, the buy-off value of privacy is determined for all individual relevant types of privacy for the case of pay-as-you-drive (PAYD) insurance PAYD insurance is an automobile insurance whereby the premium is dependent on the actual car-use Most common used indicators for car-use are mileages, and driving behavior

Respondents are willing to sell their privacy of location and space through continuously disclosing the GPS-location of their car for a financial compensation of €2,27 per month Privacy of behavior and actions appears to have slightly higher buy-off value since respondents are willing to continuously provide insight in their car-acceleration, car-deceleration and steering behavior, for a financial compensation of €2,98 per month

Regarding the privacy of data and image two buy-off values are determined related to the internal and external (secondary) use of personal information Hereby, secondary use is operationalized as the unauthorized use of personal information for personalized advertisement Respondents are willing to sell their privacy of data image for third party advertisement for a financial compensation of €2,77 per month In contrast to the external use of personal information, respondents are willing to pay a monthly contribution of €2,91 for internal (insurance related) personalized advertisement However, these outcomes cannot blind be generalized to the entire population, it can be concluded that respondents derive more disutility from external use of privacy related information than internal use

Discussion and conclusion

In conclusion, we can say that privacy concern are likely to rise with the use of mobile insurance

services However these concerns can be compensated by both perceived usefulness of the service and an expected monetary benefits The compensation by the expectation for financial benefits appears to have a smaller effect than compensation by elevated perceptions on the usefulness of a mobile insurance service

However when the expectation on monetary benefits is amplified with a financial compensation, the buy-off values for different types of privacy appear to be rather small Hereby, consumers perceive their privacy of behavior and action as more valuable than their privacy of location and space Regarding privacy of data and image, the buy-off value seems to be dependent on the one who exploits their data; the data holder or an external party While the use of consumers’ personal information for personalized advertisement by the data holder appears to be beneficial, personalized advertisement by third parties is perceived as adversely

This study is the first attempt in literature in which the buy-off value for different types of privacy is determined As this study proves, is the buy-off value of privacy varying for different types of privacy, supporting its plurality A plural approach on privacy could provide a more detailed method for future technology acceptance studies Emerging trends, such as the ongoing digitalization, quantified-self, internet of things and big data require the disclosure of different sets of personal and contextual information Consequently, different types of privacy may be involved affecting consumer adoption

to another extent Therefore, it is recommended to include a plural construct of privacy in future technology acceptance studies Further research is recommended to evaluation the value of privacy for other mobile (insurance) services A comparison between the values of privacy of these individual services may result in interesting insights for technology adoption and privacy literature

By proving the existence of multiple types of privacy dependent on the specific characteristics of concerned (mobile) services, this study validates the findings of Nikou (2012) that IT artifact should no longer be treated as ‘Black-Box’ Further, analysis methods such as factor analysis and structural equation modeling (SEM) have not been applied in the explorative survey By applying SEM in further research on the explorative dataset to examine both the effect of individual constructs per categories

of mobile insurance and a generic constructs on the likelihood of use, could result in interesting insights, in line with Nikou’s (2012) findings, that IT artifact should no longer be treated as ‘Black-Box’

Contents

Acknowledgements i

Management summary: iii

List of Figures x

List of Tables xi

1 Research introduction 2

1.1 Problem introduction: Mobile technologies as enabler for business innovation 2

1.2 Knowledge gap: The value of privacy 3

1.3 Research objective 4

1.4 Research questions 4

1.5 Research scope 6

1.6 Research approach 7

1.7 Report structure 9

2 Domain: Insurance 11

2.1 The insurance industry 11

2.1.1 The concept of insurance 11

2.1.2 Key stakeholders 11

2.1.3 Types of insurance 12

2.1.4 The insurance value chain 13

2.1.5 Insurer’s revenue model – collective goals for mobile insurance 13

2.2 The concept of Mobile insurance 15

2.3 Identification of mobile insurance services 17

2.3.1 Exploration method 17

2.3.2 Composing a long-list of mobile insurance services 18

2.3.3 Categorization of mobile insurance services 18

2.3.4 Category validation 21

2.4 Domain conclusion 22

3 Relevant Theories and Concepts on Privacy 24

3.1 Search strategy 24

3.2 The concept of privacy 26

3.2.1 Defining privacy 26

3.2.2 Measuring privacy as a concern 29

3.2.3 Types of privacy 29

3.3 Privacy and technology 33

3.3.1 Categorizing privacy harm 33

3.3.2 Technology enabling privacy harm 34

3.4 Theory applied: Involved privacy types with MI 36

3.5 Hypothesis development 37

3.6 Theory conclusion 39

4 Survey research design 42

4.1 Explorative assessment to the effect of PC, PU and MB on likelihood of use 42

4.1.1 The survey and sample design 42

4.1.2 Survey operationalization 45

4.1.3 Validity and testing of assumptions 47

4.2 An extensive assessments to the buy-off value of CSMIS related privacy concerns 49

4.2.1 Case selection: PAYD insurance 49

4.2.2 Background on conjoint analysis 50

4.2.3 The survey and sample design 52

4.2.4 Defining the attributes and attribute levels 54

4.2.5 Composition of the choice sets 56

4.2.6 Data processing and analysis 57

4.2.7 Reliability and validity 57

5 Analysis and results 60

5.1 Explorative analysis 60

5.1.1 Data processing and analysis 60

5.1.2 Descriptive analysis 60

5.1.3 Hypotheses testing 63

5.1.4 Conclusion and discussion on the results of the explorative study 65

5.2 Conjoint analysis 68

5.2.1 Estimated coefficients 68

5.2.2 Part worth utilities 69

5.2.3 Willingness to pay 70

5.2.4 Buy-off value for privacy 71

5.2.5 Influential factors for the buy-off value of privacy 72

5.2.6 Conclusion and discussion on the results of the conjoint study 74

5.3 Cross-survey comparison of results 77

6 Discussion and conclusion 79

6.1 Main findings 79

6.2 Implications 82

6.2.1 Theoretical implications 82

6.2.2 Managerial implications 83

6.3 Limitations and further research 83

6.4 Reflection on research process 85

Literature 87

7 Appendices 93

A: Long list Mobile Insurance 94

B: Literature background 97

C Hypotheses overview 102

D Surveys 103

D1 Explorative survey 103

D2 Conjoint survey 115

E Multiple regression 121

E1 Validation an verification 121

E2 Descriptive statistics (Multiple regression) 131

E3 Hypotheses testing 132

E4 Estimation General model 140

F Conjoint analysis 142

F1 Effect coding 142

F2 Ngene 142

F3 Biogeme 143

F4 Output Biogeme output 145

8 Scientific article 146

List of Figures

Figure 1.1: Research approach 8

Figure 1.2: Report outline 9

Figure 2.1: Classification insurance industry 12

Figure 2.2: The insurance value chain 13

Figure 3.1: Solove's Taxonomy of Privacy (D Solove, 2006) 34

Figure 3.2: Conceptual model 38

Figure 4.1: Explorative survey representation (age & education) 44

Figure 4.2: Correlation driven kilometers and amount of damages (Vonk et al., 2003) 49

Figure 4.3: Conjoint survey representation (age & education) 53

Figure 4.4: Survey experience by respondents 54

Figure 4.5: Ngene syntax 56

Figure 4.6: Biogeme utility functions 57

Figure 5.1: Rating on likelihood of use 61

Figure 5.2: Rating on perceived usefulness 14 61

Figure 5.3: Rating on expected monetary benefits 62

Figure 5.4: Rating on privacy concerns 15 63

Figure 5.5: Utility graph for the attribute relative consumer saving 69

Figure 5.6: Willingness to sell privacy 76

Figure 7.1: Normality check on error terms 127

Figure 7.2: Linearity check all indicators 130

Figure 7.3: Biogeme interface 143

Figure 7.4: Biogeme MODfile 143

Figure 7.5: Biogeme DATfile (example) 144

Figure 7.6: Biogeme REPfile 145

List of Tables

Table 0.1: Overview assessments v

Table 1.1: Overview of examined sub-questions per chapter 5

Table 1.2: Research scope 6

Table 2.1: Exploration sources Mobile Insurance services 17

Table 2.2: Categorization of MI 20

Table 2.3: MI Workshop Deloitte participants (27-10-2014) 21

Table 3.1: Search engines and search terms used for this study 24

Table 3.2: Concepts of privacy 28

Table 3.3 Seven Types of Privacy (Finn et al., 2013) 32

Table 3.4: Overview hypotheses 40

Table 4.1: Overview (sub) hypotheses 45

Table 4.2: Overview of MI categories with survey examples 45

Table 4.3: Overview of constructs and their operationalization in English and Dutch 46

Table 4.4: Attribute levels for privacy 54

Table 4.5: Attribute levels for relative consumer saving 55

Table 4.6: Conjoint attributes and attribute levels (Dutch) 56

Table 4.7: Model consistency verification 58

Table 5.1: Standardized coefficients (Beta) for dependent variable Likelihood of use ,, 63

Table 5.2: Hypotheses testing 64

Table 5.3: Generic model 66

Table 5.4: Estimated coefficients 68

Table 5.5: Part worth utilities 69

Table 5.6: Monetary value of utility points 70

Table 5.7: Monetary value of non-financial attributes 70

Table 5.8: Monetary value of financial attribute levels 71

Table 5.9: Comparison of utilities on influential factors 72

Table 5.10: Comparison of buy-off values (willingness to pay) on influential factors [euro] 72

Table 5.11: Privacy buy-off values for the case of PAYD insurance 74

Table 7.1: Long-list Mobile Insurance 94

Table 7.2: Involved privacy types per category of MI 100

Table 7.3: Hypotheses subdivision per MI category 102

Table 7.4: Group statistics Online/Offline experiment 121

Table 7.5: Independent Samples Test (Offline/Online) 123

Table 7.6: Multiple regression on C7 (only offline) 125

Table 7.7: Multiple regression on C7 (only online) 126

Table 7.8: Frequency statistics (skewness and kurtosis) 127

Table 7.9: Descriptive statistics Explorative assessment 131

Table 7.10: Multiple regression C1 132

Table 7.11: Multiple regression C2a 133

Table 7.12: Multiple regression C2b 134

Table 7.13: Multiple regression C3 135

Table 7.14: Multiple regression C4 136

Table 7.15: Multiple regression C5 137

Table 7.16: Multiple regression C6 138

Table 7.17: Multiple regression C7 139

Table 7.18: Multiple regression generic model 140

Table 7.19: Fit generic model 141

Table 7.20: Conjoint analysis effect coding 142

Table 7.21: Ngene choice set 142

1 Research introduction

This chapter introduces the significance of privacy concern mitigation, in the development of mobile insurance services The subsequent sections elaborate on the objective, scope, approach and research questions of this study

1.1 Problem introduction: Mobile technologies as enabler for business innovation

Since internet gained ground in the later nineties the digital revolution rapidly penetrated deep into society and transformed the way people communicate, work and live The internet gave social life an entirely different meaning and radically changed the way business was done Easier and more efficient online communication channels were born and a more online oriented consumer market arose (Pantano & Viassone, 2014) Today 87% of Dutch population uses internet on daily basis and 75% uses internet for commercial purposes (Stichting Internet Domeinregistratie Nederland, 2012) The digital revolution penetrated into the insurance sector as well Almost all Dutch insurers rolled out online platforms and 64% of them even launched a mobile platform (Deloitte, 2014)

Ongoing digitalization both results in threats as opportunities for the insurance sector Increased transparency stimulates switching behavior and shifts the insurance market to a more price based competition (Libbenga, 2013) Together with recent developments as the ban on intermediary commissions and the separation of banking and insurance activities, the traditional business model is put under pressure Given market circumstances Dutch insurers should carefully consider how to differentiate themselves in a world of continued (digital) disruption

By fully reaping the benefits of mobile technologies, such as portability, social interactivity, context sensitivity, connectivity and individuality, a variety of opportunities for innovative insurance services arises (Klopfer, Squire, & Jenkins, 2002) A more differentiated product portfolio can shift the price based competition to a more quality focus which enables insurers to operate in more niche markets focusing on higher margins (Granados, Gupta, & Kauffman, 2008) For example; Allstate (US) uses mobile technologies in their Drivewise program to offer car insurance policies in which premiums are calculated on the basis of driven miles and driving behavior; and BNP Parisbas Cardif (Italy) enhanced damage control by providing home-policy-owners with accident detection technologies Nevertheless, minimal innovative applications of mobile technologies exist within the Dutch insurance market and the applications that are present mainly serve as an additional distribution channel (Berdak & Carney, 2014; Deloitte, 2014b)

In the last few years, privacy concerns associated with the consumer use of mobile technologies, have been the subject of many research papers A number of privacy studies empirically verified the negative effect of perceived privacy concerns on the intention of use online and mobile services (Malhotra, Kim, & Agarwal, 2004; Miyazaki & Fernandez, 2001) As the disclosure of personal information is often necessary in obtaining online and mobile services, privacy concerns could inhibit people’s intention to use them as well This could have major implications for the adoption of mobile insurance since privacy concerns regarding the insurance industry are already relatively high in general (Cheung, 2014; Milne & Boza, 1999) Therefore, it is essential, in the development of future mobile insurance services, to understand the role of associated privacy concerns Accordingly, this study aims

to increase understanding of mobile insurance related privacy concerns, its relation on consumer’s

‘likelihood of use’ and potential compensating factors

1.2 Knowledge gap: The value of privacy

Today, a wide range of Dutch mobile banking services is present, however minor mobile applications exist in which financial services are directly sensitive to the user’s context Hereby, context sensitivity

is defined as ‘the ability to both gather and respond to real or simulated data unique to current

location, environment, and time of the user’ (Klopfer et al., 2002) Examples of context sensitive mobile

services (CSMS) are, the use of (user’s) GPS-location for navigations services or (user’s) browse history

as input for personal advertising (Google’s search engine) Current mobile financial services, including aforementioned Dutch mobile banking services mainly function as an extension of existing online platforms, reaping the benefits of mobile technologies as portability, individuality and connectivity, but disregarding the potential of context sensitivity

The rapid mobilization of technology in today’s society, cleared the path for Context Sensitive Mobile Services (CSMS) As the name suggests, are CSMS using user’s context information as input for its service Compared to e-commerce and not-context-sensitive mobile services, CSMS requires users to disclose extensive sets of personal information such as GPS-location, acceleration and social networks

In line with previous research, this could result in elevated privacy concerns since Bansal, Zahedi, & Gefen (2010) show us that the sensitivity of disclosed personal data has a significant positive effect on related privacy concerns Thus, the disclosure of more sensitive personal data, such as with the use of CSMS, could result in elevated privacy concerns

As the disclosure of contextual information seems to be an unavoidable condition in obtaining innovative (next-level) insurance services, privacy concerns are likely to rise with the use of mobile insurance Hereby ‘Mobile Insurance’ (M-insurance) is defined in this study as mobile technology-based insurance services, in which CSMS is integrated A number of privacy studies empirically verified the negative effect of perceived privacy concerns on the intention of use online and mobile services (Malhotra et al., 2004; Miyazaki & Fernandez, 2001) Therefore, it is assumed that related privacy concerns negatively affect consumer’s intention to use mobile insurance

Previous research of Laufer and Wolfe (1977) suggests that individuals perform a “calculus of behavior” to assess the consequences of providing personal information On the basis of this theoretical construct, individuals consider a trade-off between perceived benefits and sacrifices of disclosing personal information This implies that unavoidable privacy concerns, associated with the use of mobile insurance, have to be compensated in order to persuade consumers to adopt Hann, Hui, Lee & Png (2007) state that organizations can mitigate this negative effect of privacy concerns on the ‘likelihood of use’ in two ways; (1) by offering privacy policies regarding the handling and use of personal information and (2) by offering benefits such as monetary rewards or convenience Li, Sarathy, & Xu (2010) further operationalized these compensating benefits as ‘monetary benefits’ and

‘perceived usefulness’

A number of studies to the relation of privacy concerns on consumer’s ‘likelihood of use’ endorsed the compensating effect of ‘monetary benefits’ and ‘perceived usefulness’ in an e-commerce environment (Dinev & Hart, 2006; Hann et al., 2007; Laudon, 1996; Li et al., 2010) People are willing

to disclose personal information, as long as the benefits overrun the privacy sacrifice Although literature to e-commerce related privacy concerns, its relation on consumer’s ‘likelihood of use’ and potential compensating factors are present in literature, the effect of CSMS related privacy concerns

is still unclear The use CSMS in mobile insurance requires users to disclose more sensitive sets of personal information, which could accelerate the effect on related privacy concerns (Bansal et al., 2010) Thereby, are privacy concerns regarding the insurance industry and its online platforms already high in general (Cheung, 2014; Milne & Boza, 1999) Therefore the insurance industry environment is likely to be more sensitive to privacy issues

Insight in mitigating factors for CSMS related privacy concerns is essential in the development of mobile insurance services However, to my best knowledge no literature focusses on the perception

of privacy and mitigating mechanisms in the use of (insurance) CSMS exists Therefore, this study will assess aforementioned construct, in which the negative effect of privacy concerns on consumer’s likelihood of use is compensated by monetary benefits and usefulness, for the insurance CSMS

1.3 Research objective

Based on the knowledge gap and problem statement, the research objective is composed The research objective will function as input for the composition of the research questions

The objective of this research is to further develop understanding towards the mitigating effect of

perceived usefulness and monetary rewards on privacy concerns regarding the likelihood of use for mobile insurance services 1

Hereby, it should be noted that a single concept for mobile insurance not exists, as the term serves as

a container definition for a broad range of insurance applications based on mobile technologies Recent studies show us that privacy concerns are situation-specific, which implies that a single assessment to mobile insurance related privacy concerns is rather difficult (Margulis, 2003; D Solove, 2006) Therefore, this study will assess privacy concerns and mitigating relations per category of mobile insurance applications

1.4 Research questions

In order to achieve aforementioned research objective this section provides the research questions of this study Derived from the problem statement and the objective of this research, the following main research question (RQ) is proposed:

RQ In what way can privacy concerns, affecting the likelihood of use mobile insurance services,

be mitigated by expected monetary benefits and perceived usefulness?

In order to answer the research question, multiple sub questions are composed, embodying both theoretical as practical aspects of the study All composed sub questions incorporate some practical aspects The theoretical aspect of this study is mainly reflected in the second sub question The composed sub questions (SQ) accompanied by a brief argumentation are provided below Table 1.1 provides an overview of examined sub-questions per chapter

Since privacy concerns cannot be assessed for mobile insurance in general (section 1.3), a subdivision

of mobile insurance is required By identifying and categorizing existing mobile insurance services on its functional characteristics, privacy concerns could be assessed per individual category Therefore, sub question 1 is formulated as follows:

SQ1 Which categories of consumer insurance services based on mobile technologies can be

Central to this study is the concept of privacy Literature on privacy provides definitions, measures, subdivisions and relations to assess the mitigating effect on privacy concerns related to mobile insurance In order to incorporate relevant privacy literature in this study, sub question 2 is formulated

as follows:

SQ2 What is privacy and how is it related to perceived usefulness and monetary benefits?

Since the term ‘mobile insurance’ serves as a container definition for a broad range of insurance services based on mobile technologies, and privacy concerns are situation-specific (Section 1.3), privacy (relations) need to be assessed per individual mobile insurance category However, this study is bound

to time constraints, which excludes extensive individual assessments per mobile insurance category Nevertheless, individual assessments could be relevant for insurance companies in the composition of future product portfolios Therefore, an explorative assessment is conducted in which the mitigating relations of privacy concerns are explored for each category of mobile insurance (SQ3) Hereby, it should be explicitly noted that the ambition level of this assessment is purely explorative and outcomes have to be interpret with care

SQ3 To what extent are privacy concerns, perceived usefulness and expected monetary benefits

affecting the likelihood of use of mobile insurance services?

Elevated privacy concerns are inevitable with the use of certain mobile technologies (Chorppath &

Alpcan, 2013) Aforementioned literature by Hann, Hui, Lee & Png (2007) states that these concerns

can be compensated by means of monetary benefits or perceived usefulness Although the insurance provider could influence the customer perception on usefulness by both service characteristics as market positioning (marketing) (Davis, 1989), monetary compensation is relatively easier accomplished Therefore, an extensive assessment will be conducted towards the compensating effect

of “monetary benefits” on “privacy concerns” for one mobile insurance service (SQ4) Insight in how much monetary benefits are required to buy off inevitable privacy concerns, offers opportunities for CSMS providers to stimulate adoption through the adaption of their revenue model

SQ4 How much monetary benefits are required to buy off mobile insurance related privacy

concerns? 2

Table 1.1: Overview of examined sub-questions per chapter

1.5 Research scope

This section describes considerations regarding the scope of this study By setting boundaries in line with the research objective, the section defines the research space A schematic overview of relevant scope choices is provided in Table 1.2

To remain competitive insurers require a constant focus on business innovation (Yodokawa, 2007) Driven by a ‘mobilizing’ environment, opportunities for innovation in the insurance sector arise (Deloitte, 2014b) Mobile technologies could incentivize insurance innovation in multiple ways However, current mobile financial services mainly function as an extension of existing online platforms, reaping the benefits of mobile technologies as portability, individuality and connectivity,

but disregarding the potential of context sensitivity Therefore this study focusses on context sensitive

mobile insurance services (CSMS)

Regarding consumer insurance products basically two types can be distinguished; life and non- life insurances According to Dutch law, conditions for disbursement of life insurances are directly related

to human loss Non-life insurance, is a catchall phrase to describe almost any insurance other than life coverage, including property, casualty and health policies Life insurances are usually contracted in smaller quantities but for longer, often life-time periods while non-life insurances can be considered

as fast moving, short term products Non-life insurance is characterized by a higher claim frequency, higher reciprocity and more intensive customer interaction (Deloitte, 2014a), offering more possibilities for the involvement of mobile insurance services Hence this study will focus on mobile

product opportunities for non-life insurance

Traditionally non-life insurances were mainly distributed by intermediaries, but with the broad introduction of the internet and recent legal adjustments, as the ban on intermediary commissions and the separation of banking and insurance activities, direct sales (over the internet) became the most used distribution channel (Deloitte, 2014b) Although online insurance agents are present (e.g Independer & Hoyhoy), they mainly function as a selling partner Insurance services are still directly delivered to the customer Regarding mobile insurance, this study will therefore focus on consumer

services offered by the insurer to the consumer, disregarding mobile services for intermediaries (B-C)

Previous research shows us that efficiency improvements can be achieved with the use of mobile technologies for insurance purposes (Berdak & Carney, 2014) Less labor intensive enclosure and claim procedures, faster customer contact and easier information gathering methods can result in gains for both insurance companies as customers (Baquero Forero, 2013; Carney, 2014) For example; Achmea recently announced that they expect that with the introduction of those self-service (mobile) platforms, 4,000 employees, almost a fifth of all staff, would be made redundant (Achmea, 2013) However, mobile insurance services could have major impact on insurer’s business model, this study

focuses on consumer attitude on functionalities of mobile insurance

Table 1.2: Research scope

B-B, C-C Consumer functionalities Business efficiency gains

Application for Dutch market Application for international market

1.6 Research approach

In order to answer formulated research questions, this section provides a structured approach substantiated by multiple research methods A visual overview of described research approach and research methods is presented in Figure 1.1

For a full comprehension of the problem area, this study will commence with a context exploration

An introduction in relevant insurance processes and mobile insurance technologies is provided This information is mainly gathered by means of a desk research complemented by expert interviews, where necessary

Subsequently, an explorative identification and categorization of global practices regarding mobile insurance services, is carried out Mobile services in current, national and foreign, insurance markets will serve as an input Based on market research publications (e.g Forrester & Gartner), scientific literature and expert validation (workshops), an overview of global mobile insurance applications is composed (SQ1) These global MI application are categorized on the basis of their properties

Thereafter, relevant privacy literature will be analyzed (SQ2) Privacy is plural and within literature a single account of privacy has yet to emerge Thereby multiple types of privacy could be distinguished and privacy could be harmed in various ways These types of privacy (harms) serve as a guideline for further research steps Aforementioned privacy literature is also used to identify the types of privacy that is harmed by each category of mobile insurance applications In addition scientific literature will

be used as a foundation for the research hypotheses Hypotheses on the mitigating effect of

‘usefulness’ and ‘monetary rewards’ for ‘privacy concerns’ regarding the ‘likelihood of use’ mobile insurance products and services, will be composed in this section

Since the answer to sub question 3 and 4 reflects the attitude of consumers regarding mobile insurance, a consumer survey is subsequently conducted to answer them Hereby, two consumer

surveys are conducted to answer sub question 3 and 4 individually; an explorative and a conjoint

survey3 A (consumer) survey is a helpful data-collection method to reveal consumer attitudes and preferences regarding mobile insurance It offers the opportunity for numerous questions and a broad range of data can be collected In line with the aim of the research questions, a survey is the ideal method to get insight in the preference and attitude of the population by conducting a relative small experiment

By means of an explorative survey consumer’s attitude on mobile insurance is assessed

Consumer attitude on mobile insurance regarding ‘usefulness’, ‘monetary rewards’, ‘privacy concerns’ and the ‘likelihood of use’ provides insight in mitigating factors for privacy concerns (SQ3) Multiple regression is used to assess the effect of mitigating factors on privacy concerns for all categories of mobile insurance service Multiple regression is an appropriate method of analyses when a single metric dependent variable is presumed to be predicted by two or more metric independent variables

In order to assess how much monetary benefits are required to buy off mobile insurance

related privacy concerns, a conjoint survey is conducted (SQ4) Conjoint analysis is a statistical

approach, often used in market research to determine customer preferences and product pricing points (Green, Krieger, & Wind, 2001; Henscher, Rose, & Greene, 2005; Louviere, Hensher, & Swait, 2000) “It is a utilitarian methodology in which respondents value different alternatives or profiles by making implicit trade-offs, from which their preferences are obtained” (Green et al., 2001) Due to time constraints this research only assesses the monetary value for one individual MI practice Further elaboration on the research methodology can be found in chapter 4

Eventually, conclusion will be drawn, outcomes will be discussed and both theoretical as practical implications will be discussed

Figure 1.1: Research approach

1 Context exploration insurance & mobile

3 Literature study to types

of privacy and adoption factors for mobile insurance

services

2 Identification of categories

of insurance applications based on mobile technologies

4 Survey mobile insurance applications with consumers

7 Discussion and conclusion

5b Conjunct analysis to the value of privacy regarding one mobile insurance service

SQ4

1.7 Report structure

This section provides the structure of this report, as presented in Figure 1.2 Chapter two describes the relevant domain for this study; it gives some context information on the insurance industry, provides definition for mobile insurance and identifies and categorizes mobile insurance service Chapter three will discuss the relevant theories and concept on privacy In addition a conceptual model is developed and hypotheses are drawn Subsequently, chapter four is used to describe the research designs for the surveys and in chapter five the results are given Finally, the discussion, conclusions, recommendations, implications and reflection is provided in chapter six

Chapter 1:

Research introduction

Chapter 2:

Domain description Mobile insurance practices

Chapter 6:

Practical and theoretical implications, Conclusions, recommendations and reflection (RQ)

Methods:

Product of

chapter:

Desk Research Literature Research Interviews

Research questions Demarcation Research Methods

Desk Research Literature Research Interviews

Identification Mobile Insurance services

Desk Research Literature Research Interviews

Explorative Survey Conjoint Survey

Survey Data analysis

Hypothesis testing Survey results

Conclusion, discussion and recommendations

Chapter 3:

Relevant Theories and Concepts (SQ 2)

Desk Research Literature Research

Definition of privacy Types of privacy Hypotheses

Figure 1.2: Report outline

Chapter 2

Domain: Insurance

2.1 The insurance industry

2.2 The concept of insurance

2.3 Identification of mobile insurance services

2.4 Domain conclusion

2 Domain: Insurance

The concept of insurance is almost as old as human society In ancient civilization, if someone’s home burned down, the other members of the community would band together to help rebuild it Everyone felt duty bound to help in case their home was the next to burn Over the years, insurance grew into the form we know today, as it manages the risk to people and business Although the insurance industry of today is not recognized for being innovative, great opportunities rise with the mobilization

of technology (Berdak & Carney, 2014) This chapter will provide a brief elaboration in the consumer insurance industry of today (section 2.1.) and the mobile opportunities of tomorrow (section 2.2.) Subsequently an exploration and categorization of global mobile insurance services is provided (section 2.3.) Finally, last section provides a brief conclusion for this chapter

2.1 The insurance industry4

As a form of risk management, insurance allows, both individuals as other entities, to protect themselves against potential losses Although nowadays the concept of insurance seems to be more complex, it is still based on the same basic principles as it was centuries ago This section provides an elaboration on the basics of the insurance industry of today

2.1.1 The concept of insurance

Insurance is defined as the equitable transfer of the risk of a loss, from one entity to another, in exchange for a payment (Dorfman, 2012) In practice this comes down to a contract whereby in consideration of a premium, the insurance company agrees to cover the insured subject to agreed limit, in the event of a loss (Ibiwoye, 2011) Insurance works by pooling risks; combining the risk of a large group of people enables enhanced event estimations On individual level, risk assessments involve relative high uncertainties regarding the occurrence of specific events, while central limit theory could be applied on pooled risks, enabling fairly precise (risk) event estimations The law of large numbers tells us that the average of a large number of independent identically distributed random variables tends to fall close to the expected value (Smith & Kane, 1994) Applied on the practice of insurance, this tells us that the larger a risk pool is, the more precise risk events can be estimated A more precise expectation of risk events enables more precise premium calculations, enabling insurers to offer more competitive prices (Mackenzie, 2014) Thus, sufficient size of the risk pool is a basic condition for insurance Subsequent, involved risks need to be independent, unintentional and accidental

By pooling risk, the concept of insurance provides both benefits for consumers as insurers From a consumer perspective, insurance serves financial security and stability since future uncertainties are covered For insurance companies, insurances are their driving element of business contributing to their profit In addition to these primary benefits insurance fulfills a socio-economic role Due to the long term nature of liabilities, sizeable reserves, and predictable premiums, insurance pool-capital provides large scale reserves (Dionne & Harrington, 2014) These large scale reserves functions as economic foundation and boosts economic activity and investments In addition does the transfer and sharing of risk encourage economies to trade and invest

are directly and indirectly involved in the insurance process Involved key stakeholder are summed up bellow:

 Consumer who buy insurance product

 Insurance carriers that provide insurance coverage through policies and accept the risk covered

by the policies These are generally large insurance companies, including direct insurers and reinsurers

 Investors that support insurance companies by purchasing insurance company stock

 Partners who couple with insurance companies to share profits and losses Partners include

reinsurers, institutional investors, and trade partners Partners also include the insurance agencies and brokerages that distribute insurance products

 Outside network that include those that perform professional services for insurers They include

appraisers, insurance bureaus, reinsurers, claim adjusters and firm providing consulting, claim processing, and data collection services

 Regulators and auditors that help secure the financial health of the insurance industry Regulators

implement and enforce regulations, while auditors ensure adherence to finance and accounting standards

 Vendors that supply the good insurers require to perform business activities Examples include IT

distributors and administrative goods suppliers

Health insurance

Property insurance

Casualty insurance

Business insurance Consumer insurance

Figure 2.1: Classification insurance industry

A first distinction exists in the focus on consumer or corporate (business) entities Although corporates do use insurances to cover their liabilities, the nature and size of the risk can be a reason

to insure in-house For instance, companies who own a sizeable car-fleet not insure their fleet but bear the risk themselves Again the law of large numbers can be applied and risk is pooled However,

as the scope indicated, is this study focused on consumer insurances Regarding consumer insurance basically two types can be distinguished; life and non- life insurances According to Dutch law, conditions for disbursement of life insurances are directly related to human loss Non-life insurance,

is a catchall phrase to describe almost any insurance other than life coverage, including property, casualty and health policies Life insurances are usually contracted in smaller quantities but for longer, often life-time periods while non-life insurances can be considered as fast moving, short term products

Non-life insurance is characterized by a higher claim frequency, higher reciprocity and more intensive customer interaction (Deloitte, 2014a), offering more possibilities for the involvement of mobile

insurance services As mentioned, non-life insurance includes a broad range of policies with consumers throughout all segments of population However, the focus of these policies show a wide difference, the characteristics of these policies have large similarities regarding structure and conditions (Rokas, 2003)

2.1.4 The insurance value chain

The insurance industry business model contains two types of activities: primary activities and support Primary activities make up the company’s value chain and support activities support the value chain Support activities may include corporate services, finance, human resources, or information systems and technology

Figure 2.2: The insurance value chain

The value chain, as presented in Figure 2.2 provides a functional model for an insurance organization

It models the various functions an organization performs without consideration for how they are performed It is through the act of defining these processes that roles and responsibilities are defined, and organizational structure comes into view The value chain describes the company’s products process from start to finish and can be considered as the product’s process cycle An organization that serves more than one type of market may have multiple value chains The following primary activities

in the insurance value chain can be distinguished:

1 Marketing: The first step in the value chain process is marketing At this point, a business must

determine which policies it will offer

2 Risk Modeling: As part of marketing, a business must determine the policy mix and pricing

strategy To determine how premiums will be calculated for each policy, the business must also perform risk modeling Using the information gathered from risk modeling, the business can then determine the actual prices for each policy

3 Sales: The business is now in a position to begin selling its insurance policies to customers

Selling involves quotations, proposals, risk assessments, and commission calculations Commissions are paid to all parties involved in the distribution channel

4 Policy Administration: Having sold a policy, the next step is to write the policy.

5 Billing: Customers can be billed once their policies have been written.

6 Claims: Customers who have paid their premium may at some point make a claim This activity

is optional, however, as customer may never make a claim

7 Customer Service: The customer service activity involves serving the needs of customers until

their policies expire

2.1.5 Insurer’s revenue model – collective goals for mobile insurance

A concise and simplified representation of the revenue and cost flow of the insurance business model

is provided below:

Profit insurer = earned premium + investment income – incurred loss – underwriting expenses

This profit formula depicts the revenue and cost flow of the insurance business model Money comes from earned premiums and investment income and goes to incurred loss and underwriting expenses

A short elaboration on the individual aspects of the insurance business model is provided below:

Earned premium, a source of income, is the total of all the premium payments received by an insurer

for the current coverage period Premiums could only be considered as “earned” at the end of a policy period Conflicting interests between insurance carriers and undertakers emerge regarding the height

of the insurance premium Higher fees benefit the profit of insurers but negatively affect the costs for the undertaker In a competitive insurance market, supply and demand will set an equilibrium, dealing

with this conflicting interest A second revenue flow is generated by investment incomes Investment

income is the residual income generated as a result of investing pool capital in the capital markets This also includes annuity considerations and asset earnings Both insurers as undertakers gain advantage of high investment incomes, however investment incomes are dependent on investment strategies and external forces such as the economic climate

Insurer’s profit is negatively affected by the incurred loss and underwriting expenses Incurred loss is

the sum of all claims paid, adjusted by the change in claims reserve and related claim expenses for the

same accounting period Underwriting expenses include all the costs associated with a policy, including

commissions and the portion of administrative, general, and other expenses attributable to underwriting From macro-economic perspective the insurer and undertaker share the goal to reduce the cost flow Reducing the cost flow in the insurance business model results in both space for higher profit margins as better, more competitive rates

The effect of mobile insurance on the revenue model

In order to reduce the costs flow, major opportunities arise for mobile insurance technologies By optimizing and automating insurance processes, such as sales-, contract- and claim activities, efficiency gains could be achieved and underwriting expenses could be minimized (Berdak & Carney, 2014) In addition significant benefits could be gained regarding the incurred losses The incurred loss

is the product of risk event probability and risk event impact (Deloitte, 2014a) Reducing probability and impact both results in lower incurred losses The risk probability of the risk pool is based on the composition of individual risks By accepting only low risk policies, the overall incurred loss could be reduced Globally, insurers attempt to fine-tune their insurance conditions such that risk profiles are

as low as possible Examples exist regarding health insurances exclusively focused on young people Mobile technologies could provide rich data bases, enabling insurers to enhance their risk assessments and risk pooling In addition, progressive insurers even attempt to increase risk awareness among their existing customers to keep risk probabilities as low as possible

Many insurers go even further and attempt to decrease impact, in case a risk events occurs, by providing their customers with specific knowledge; what to do in case of a coming hurricane or an accident abroad Mobile technologies offer a range of opportunities that support insurers to lower their incurred loss Further elaboration on these mobile technologies is provided in following sections

2.2 The concept of Mobile insurance

Although the insurance industry of today is not recognized for being innovative, advanced mobile technologies offer great opportunities (Berdak & Carney, 2014) Emerging technologies enable innovative insurance services to change traditional contact moments and customer interaction In preparation for a global exploration of mobile insurance services, this section introduces the concept

of mobile insurance; how is it defined and what does it include

In this study the term mobile insurance (MI) is used to describe a broad range of insurance products and services based on mobile technologies An elaboration on the concept of insurance is already provided in previous chapter Subsequently, mobile technologies have been defined in literature as

“wireless devices and sensors (including mobile phones) that are intended to be worn, carried, or accessed by the person during normal daily activities” (Kumar & Nilsen, 2013) This definition stretches the application of mobile technologies to a further extent than just mobile phones or tablets and includes all kinds of wireless devices and sensors Aforementioned definition of Kumar et al (2013) is mainly focused on the portable aspect of ‘mobile’ In order to create a more common understanding

of mobile technologies Klopfer, Squire & Jenkins (2002) draw up five features of mobile devices:

1 Portability – as included in Kumar et al.’s definition this covers the ability to move from one

place to another

2 Social interactivity – the ability to exchange data and collaborate with other people face to

face

3 Context sensitivity – the ability to both gather and respond to real or simulated data unique

to current location, environment, and time

4 Connectivity – the ability to connect to data collection devices, other devices or to a common

network Gathered data could be shared or external information could be received via such a

connection

5 Individuality – the ability to provide unique services that are customized to the individual’s

path of investigation

The combination of insurance and above-mentioned features of mobile devices could lead to a range

of innovative insurance services However, Dutch insurers already put their first steps into the mobile world, several opportunities are still unexploited Currently, Dutch insurers mainly exploit mobile technologies as an extra communication channel disregarding the potential of social interactivity and context sensitivity Existing mobile insurance services are mainly embodied by apps for phone or tablet, exploiting mobile features as portability, connectivity and individuality Depending on their particular application, these apps mainly provide static/dynamic policy information, (cross-) sales opportunities and claim management

The broad integration of advanced mobile sensors is thereby offering increased opportunities for context sensitive mobile opportunities (Doulkeridis & Vazirgiannis, 2008) Since progressive application of mobile technologies, which reap the benefits of context sensitivity as well, are absent

in the Dutch insurance industry, this study is mainly focused on these features In particular, the use

of context sensitive mobile service (CSMS) offers large sets of extra input for innovative insurance services

Therefore, mobile insurance services, also referred to with just mobile insurance, is defined as

insurance products and services based on context sensitive mobile technologies Hereby insurance

products and services involve all direct customer focused activities of an insurer Thus, both the

insurance policy itself and supportive services are involved Context sensitivity of mobile technologies

involves the ability to both gather and respond to real or simulated data unique to current location, environment, and time

2.3 Identification of mobile insurance services

Since it is assumed that consumer attitudes cannot be assessed for mobile insurance in general (section 1.3), a subdivision of mobile insurance is required In order to subdivide mobile insurance this section provides a global exploration and categorization of existing mobile insurance services These categorized services will serve as an input for a survey among Dutch consumers to assess their attitude

on mobile insurance First, section 2.3.1 elaborates on used sources and search techniques to identify existing mobile insurance services Based on the saturation principle a long-list is composed in section 2.3.2 Eventually, all listed mobile insurance services are categorized on their main consumer functionalities to eight categories These categorization is presented in section 2.3.3 and validated in

section 2.3.4

2.3.1 Exploration method

As a first step in the identification of global mobile insurance services, the exploration method is determined Since no unified global definition for the concept of mobile insurance exists, a variety of inexhaustible sources is available, and this study is conducted under tight time constraints, exclusive identification of existing mobile insurance services is unattainable Therefore the identification of existing mobile insurance services is based on the saturation principle

Saturation principle

Saturation is the point in data collection when no new or relevant information emerges with respect

to gathered data (Saumur & Given, 2008) With respect to this study, the saturation principle implies that the exploration to mobile insurance services is completed, when no unique mobile insurance service, compared to already listed MI services, can be found

Exploration sources

A variety of information through various sources such as journals, theses, conference proceedings, reports, newspapers, business publications, market scans, industry expert reviews and the internet is available Forced by time constraints, the initial search strategy was focused on existing market overviews and trend reports Valuable and recent information was mainly provided by industry experts, industry journals and industry websites such as Insurance&technology.com Table 2.1 provides an overview of major used sources and search term combinations

Table 2.1: Exploration sources Mobile Insurance services

Identifying mobile insurance services

 Google scholar, Science direct, Scopus

 Google search

 Google play, Apple iTunes

 Gartner, Forrester

 Deloitte Experts

 “Innovative”, “mobile”, “connected”, “future

“wearable(s)”, “location”, “context”

 “insurance”, “service”

 “home”, “car”, “health”

 “service”, “product”, “application”,

“innovation”, “discount”

 “CSMS”, “context”, “SMART”

2.3.2 Composing a long-list of mobile insurance services

Before an identified mobile insurance service is added to the long-list it has to meet certain conditions: First, the service has to be characterized by insurance aspects as mentioned in section 2.1 Thereby the service has to be focused on consumer functionalities and must be deployable by an insurer himself (i.e no intermediary services or inter-insurance price comparisons) Second, the practice must

be characterized by the aspect of context sensitivity (CSMS) as mentioned by Klopfer et al (2002) in section 2.2 Third, identified mobile insurance services has to be unique, compared to already listed

MI services, before being added to the long-list (saturation principle) This way, the long-list of mobile insurance services includes only unique mobile insurance services

Long-list mobile insurance services

The exploration of mobile insurance services eventually took five days of fulltime work The composed long-list of 53 MI services is attached to this report in appendix A Next paragraph describes the categorization process of these mobile insurance services

Remarkable observation

During the exploration of relative many Pay-As-You-Drive (PAYD) initiatives are observed With PAYD insurance actual driving behavior is used as input for variable premium calculation Depending on individual insurance policies driving behavior is defined as driven kilometers or acceleration behavior

2.3.3 Categorization of mobile insurance services

Now a long-list of global mobile insurance services is provided, next step is to categorize them These categorized services will serve as an input for a survey among Dutch consumers to assess their attitude

on mobile insurance Categorizing MI services is necessary since too many practices are identified to assess them individually in a survey

Categorizing mobile insurance services

The categorization is based on the main functionalities of the mobile insurance services In order to fully cover all mobile insurance services consistently, the MI services are categorized through an iterative process Through this iterative process, the categorization is revised and validated with experts in multiple rounds Subsequent section elaborates further on the category validation Table 2.2 provides an overview of defined categories of mobile insurance services, including user functionality and their effect on the insurer’s revenue model This categorization is even integrated in aforementioned long-list provided in appendix A Subsequent to the categorization a brief elaboration

on identified categories of mobile insurance is provided

1 Usage based insurance

Usage based insurance (UBI) includes insurance policies in which premium calculation is based on actual use Most common application of UBI involves kilometer-dependent car policies in which

premium calculation is based on actual use (e.g driven km) Globally a growing number of insurers embrace this concept in their new line of car insurances UBI mainly comes with a GPS location tracker, which discloses driven mileage or location details to the insurer However some insurers offer the UBI concept based on manual mileage registration, in which the user manually discloses his driven kilometer to the insurer, disregarding a GPS location tracking system

2 Behavioral rewarding

With behavioral rewarding (BR), customers can earn discounts on their premium or additional benefits

by behaving safe and secure This way, BR stimulates people to reduce the risk of an accident risk and incurred losses could be minimized

With the rise of wearable technologies, the monitoring of health and sport records is emerging Data provided by these devices could provide input for BR initiatives within the health insurance industry First trends regarding health policies in which sport and health records serve as an input for a rewarding system have been observed, however no existing policies incorporated the use of connected wearable technologies yet

More observed, is the incorporation of BR in car policies Facilitated by connected sensors (G-sensor), car drivers’ acceleration is measured and transmitted to the insurers Now, insurance carrier provide their users with discount for easy and safe acceleration behavior Globally, several BR initiatives for car policies have been launched In the Netherlands the first BR initiative has been launched in the beginning of 2014 by Whoosz

motion-3 Up-to-date insurance package

Based on personal information and/or context sensitive input, such as phone GPS-location or social media input, users will be provided with relevant insurance offerings For example, a travel insurance

is offered on the moment you cross a border Increased social media integration and the rise of context aware mobile technologies facilitate up-to-date insurance packages Besides the use of context aware information, up-to-date insurance package could be facilitated by enhanced data analysis (big data) This data gathering method however falls out of scope for this study

4 Preventative information services

Based on user specific information, such as GPS-location, users are provided with advisory messages With the provision of preventative messages, insurance carriers increase risk awareness and improve damage control Observed practices are rainfall alerts for farmers, helpful push messages for travelers abroad in case of a threating situation and indicator for driving behavior after the use of alcohol

5 Accident detection & prevention

Accident detection & prevention differs from up-to date insurance package since no additional insurance policies are involved and from preventative information service since it does not regard the consultation of policy-holders With accident detection and prevention the insurers facilitates or stimulates the use of mobile technologies to monitor and act on happened or coming accidents By detecting an accident as quick as possible, damages could be controlled and incurred losses are minimized For instance, BNP Parisbas Cardif (Italy) provides home-policy-owners with accident detection to detect leakage, overvoltage and fire at the time of the event to act accordingly Observed initiatives on car policies in the United States go even further with the provision of collision avoidance systems By detecting a collision before it even happened, damage could be prevented and risk of an accident is minimized

6 Mobile accessibility

Mobile policy management offers users the ability to manage existing and new insurance policies anywhere and anytime Adapt the coverage of an open policy or open a new one Facilitated by the use mobile apps mobile policy management serves as a sales distribution channel for insurers

In addition, mobile claim management offers users the opportunity to claim files everywhere and anytime Growing numbers of insurers, mainly in the car insurance industry, offer user mobile claim management as an extra service In addition to the increase customer service, efficiency gained could be obtained for the insurer by optimizing the claim process Most current applications of mobile

accessibility involve the use contextual information to validate claims, however not all application involve user contextual information

7 Personal dashboards

The use of personal dashboards, offer users the opportunity to have insight in their actual behavior

By presenting overviews of users’ context information, such as driving behavior or sport records, risk awareness could be increased Research by Toledo & Lotan (2006) shows us that drivers, with insight

in their actual driving behavior tend to drive more safe and secure Personal dashboards often come together with UBI and BR insurance applications

Personal dashboards are mostly used in combination with social ranking Insurers realized that striving for being the best is in human nature They used this social mechanism by incorporating it in

a social game for being the safest, cleanest or most efficient driver Now people can share their driving skills and battle against each other to be the best Social ranking motivates people to behave more safe and secure, minimizing accident risk

8 Additional Informative services

Mainly through the use of mobile apps, a broad range of informative services is provided by insurers From apps that provide insight in your policy conditions and claim history, to games that increase risk awareness; insurers developed a lot of mobile informative services in order to boost sales, increase risk awareness and improve damage control As subcategory, serious games are offered by insurers; educational games with the goal to change people’s behavior In order to provide more accurate information, informative services increasingly use contextual information, such as GPS-location, as input For example to locate the nearest car garage or medical expert

Aforementioned categories of Mobile insurance including their effect on the insurer’s revenue model are summarized in Table 2.2:

Table 2.2: Categorization of MI

revenue model:

(variable insurance premium per driven km)

Earned premium (-/+)

(driving-behavior/ healthiness lifestyle)

Earned premium (-), Incurred loss (-)

adjustments & In-App filing and tracking of claims

Underwriting expenses(-)

car efficiency Compare your (driving) efficiency with your relatives and challenge to be the best

Incurred loss (-), Underwriting expenses(-)

2.3.4 Category validation

As aforementioned, an iterative categorization process is used to cover the field of existing global MI services as complete as possible In order to enclose existing services in best fitting categories, experts are involved, throughout the categorization process Selected experts are chosen within the organization of Deloitte for their years of experience and proven expertise in the field of digital insurance industry and insurance innovation

By means of two stages the categorization is validated:

1 By means of two individual real-life meetings comments were discussed and categories were adapted with two groups of experts In the validation of these categories, the long-list and categorization was send in advance Initial categorization was already quite mature, however several changes has been adapted and renamed

2 Subsequently, a workshop MI is organized with several Deloitte experts in the field of Financial Service Industry (FSI), Technology Integration and Business Model Transformation (BMT) (see Table 2.3) The workshop had two purposes; validating the MI categorization and discussing the explorative survey questionnaire (section 4.1) With respect to the category validation, minor adaption has been made

Table 2.3: MI Workshop Deloitte participants (27-10-2014)

Participant 1 Partner Technology Technology Integration//FSI

Participant 2 Director Strategy & Operations BMT/FSI

Participant 3 Senior Manager Strategy & Operations BMT/FSI

Participant 4 Senior Manager Strategy & Operations BMT/FSI

Participant 5 Senior Manager Intern General marketing

Participant 6 Senior Manager Technology Technology Integration//FSI

Participant 7 Manager Technology Technology Integration

Participant 8 Consultant Technology Technology Integration//FSI

For a clear and consistent understanding of this research question the definition of mobile insurance

for this study is provided Mobile insurance services, also referred to with just mobile insurance, are insurance products and services based on context sensitive mobile technologies Hereby insurance

products and services involve all direct customer focused activities of an insurer Thus, both the

insurance policy itself and supportive services are involved Context sensitivity of mobile technologies

involves the ability to both gather and respond to real or simulated data unique to current location, environment, and time

In order to get a better understanding on the scope of mobile insurance, sub question 1 is used to identify relevant categories of mobile insurance This categorization is based on an explorative scan

to all worldwide mobile insurance application These worldwide mobile insurance applications are subsequently categorized on its consumer functionalities and validated with insurance industry and technology experts The final categorization, with a brief elaboration per category is listed below:

1 Usage based insurance; With a usage-based insurance premium, consumers pay only

premium for actual use of their insurance

2 Behavioral rewarding; By rewarding customers for less risky behavior, the insurer is trying

to reduce the risk of accidents

5 Accident detection &

7 Personal dashboards; By measuring individual behavior, insight could be provided in risk

profiles of consumers to increase risk awareness

8 Additional informative

services;

Context sensitive information offers opportunities for several insurance services

semi-Chapter 3

Relevant Theories and Concepts on Privacy

3.1 Search strategy

3.2 The concept of privacy

3.3 Privacy and technology

3.4 Theory applied: Involved privacy types with MI

3.5 Hypothesis development

3.6 Theory conclusion

3 Relevant Theories and Concepts on Privacy

This chapter answers the following research sub questions: “What is privacy and how is it related to perceived usefulness and monetary benefits?”(SQ2) In line with this sub question, this chapter elaborates on relevant theories and concepts regarding the research scope Since sub question 2 still contains a relative high level of complexity, this sub question is subdivided into the following four

questions:

SQ2a How is privacy defined?

SQ2b How can privacy be measured?

SQ2c What types of privacy are involved in the use of mobile insurance?

SQ2d How are privacy concerns related to perceived usefulness and expected monetary

benefits?

The first section provides insight in used sources and search techniques Next, section 3.2 provides a review on relevant concepts of privacy in scientific literature including choices on privacy definitions (SQ2a), privacy measurement (SQ2b) and an identification of privacy types Section 3.3 briefly elaborates on the relation between privacy and technology and section 3.4 identifies privacy types involved in the use of mobile insurance services (SQ2c) Finally, section 3.5 is used for hypothesis development on privacy concern compensation (SQ2d) and last section provides a brief conclusion

3.1 Search strategy

A literature review has been carried out to identify the knowledge gap and provide underlying theories and concepts for the research A variety of information through various sources such as textbooks, journals, theses, conference proceedings, reports, newspapers, business publications, industry expert reviews and the internet, is available With an aim not to reinvent the wheel, the initial search strategy was focused on articles that elaborate on related relevant topics or provide an overview of existing literature By means of the snowball method, iterative backward reference searches were performed

on existing literature reviews In addition, more recent scientific literature was obtained through forward reference searches, facilitated by Scopus Table 3.1 provides an overview of major used sources and search term combinations

Table 3.1: Search engines and search terms used for this study

Sources of information: Main search term combinations:

Identifying the literature gap:

 Google scholar, Science direct, Scopus

 Google search

 “privacy”, “privacy calculus”, “trust”, “context sensitive”,

“CSMS”

 “technology adoption”, “behavioral intention”

 “mobile insurance”, “digital”

 “literature review”, “research area’s”, “overview” or

“literature analysis”

Literature review on privacy:

 Google scholar, Science direct,

Scopus, Mendeley

 Google search

 Gartner, Forrester

 Deloitte Database (intern)

 TU Delft Library, Google books

 “privacy”, “concept of privacy”, “privacy theory”, “privacy types, “privacy taxonomy”, “location privacy”

 “value”, “trust”, “characteristics”, “concern”

 “literature review”, “research area’s”, “overview” or

“literature analysis”